A Review on Flexible Electrochemical Biosensors to Monitor Alcohol in Sweat
Abstract
:1. Introduction
2. Alcohol Biomarkers
- Ethanol: strongest and most studied validating biomarker. Ethanol has a short half-time in the organism, limiting its use to recent consumption. This biomarker can be detected in all biological matrices already mentioned [20].
- EtG (ethylglucuronide): direct metabolite of ethanol. Although it comprises only about 0.1% of the total ethanol disposal, EtG has a wide window detection, being possible to detect this substance in blood and urine up to 36 h and 5 days after excessive consumption of alcohol, respectively. Incidental exposure to ethanol-containing products and even yeast and sugar may result in false-positives [21], while false-negatives can occur with certain urinary tract infections [22]. This biomarker has shown good results for detection through other biological matrices such as sweat and hair [23]. EtG measurements for alcohol abuse in hair have a relatively high sensitivity and specificity, of 70–90 and 80–95%, respectively [23,24].
- FAEEs (fatty acid ethyl esters): represent ester conjugates between fatty acyl chains (such as oleic acid, steric acid, and palmitic acid) and ethanol. This biomarker is detected from sebum produced through the sebaceous glands [16,17]. These glands are mostly located in the hair and face. Nonetheless, can be in all areas of the body except the palms the hands and feet. These alcohol metabolites have been reported to be present in the blood for up to nearly 100 h in heavy drinkers. The biological matrices most used for the detection of this biomarker are blood and hair [26].
- CDT (carbohydrate-deficient transferrin): strong biomarker for chronic ethanol ingestion. CDT refers to the minor varieties of transferrin with lower degrees of glycosylation, including asialo-, monosialo- and disialotransferrin, which contain zero, one and two sialic residues, respectively [27]. Many versions of this glycoprotein are found in healthy people. However, studies show that consumption of alcohol increases the concentrations of this substance. The sensitivities and specificities of CDT are approximately 60–70 and 80–95%, respectively [28]. CDT levels may be influenced by other conditions unrelated to alcohol use, such as anorexia nervosa [29] and pregnancy [30]. Additionally, the measurement of CDT has been shown to be imprecise and difficult. The biological matrices most used are blood and urine [18].
- β-HEX (β-hexosaminidase): is a lysosomal hydrolase that is involved in the metabolism of carbohydrates and gangliosides in the liver. After heavy alcohol consumption, lysosomes are damaged and release the enzyme into the blood stream [31]. The half-life of β-HEX in serum is approximately 6.5 days [32]. The sensitivity of serum and urinary β-HEX activity has been reported to be 69–94 and 81–85%, respectively, while the specificity of serum and urinary β-HEX activity is 91–98 and 84–96% [32]. However, elevated serum β-HEX occurs in patients with hypertension, diabetes, cirrhosis, myocardial infarction, in pregnancy and after oral contraceptive [33].
3. Sweat as a Biological Fluid of Detection
3.1. Sweat Composition
- Sweat Released Rate: According to a study, the average sweat rate during physical activity is approximately 0.5 µL/min/cm2 with a range of 0.17 to 1.21 µL/min/cm2 [48]. When considering all areas of the skin, the resting sweat rate should be less than the sweat rate during exercise by 40% [48]. Thus, we can say that, on average, about 1.2 µL/min/cm2 corresponds to the amount released by an individual at rest. However, it’s important to note that the palm region, which is the study area, has a skin with higher density of sweat glands, adding ease of collection [49]. Furthermore, in addition to liquid phase sweat detection (sensible sweat), there are some devices capable of measuring volatile organic compounds (VOCs) released through skin (insensible sweat), that have shown high correlation with blood alcohol levels [24,25]. The two types of human sweat under normal conditions are illustrated in Figure 3.
- Contamination: Chemicals absorbed by the skin through different cosmetics can be released through sweat and interfere with detection capability. Thus, sweat should be quickly absorbed by the detection platform to avoid contamination from the skin. A way to prevent different components from interfering with the intended analyte reading is, for example, the use of a semipermeable membrane, responsible for allowing only certain substances to pass through it by diffusion [43].
- Sample Evaporation: it is necessary to have a fast detection in order to obtain reliable results, as evaporation acts quickly on small volumes of exposed sweat, which may change the concentration of its constituents [43].
3.2. Alcohol in Sweat: Correlation between Sweat and Blood
3.3. Flexible Biosensors to Detect Alcohol in Sweat
4. Biosensors
Components of a Biosensor
- Piezoelectric biosensors: are based on the piezoelectric property which the anisotropic crystals (quartz, for example) possess. When an alternated voltage is applied to this biosensor, the crystal oscillates with a certain frequency, associated with the mass and elastic constants of the crystal [67].
- Electrochemical biosensors: have the aim of generating an electrical signal that is related to the concentration of the target analyte in the sample. The chemical reactions that occur between immobilized bioreceptor and the target analyte produce or consume ions or electrons affecting electrical behavior, such as current or electrical potential [64,68].
5. Electrochemical Techniques
- Amparometric: amparometric biosensors measure the current produced due to electrochemical oxidation or reduction of electroactive species at the working electrode when a constant (in case of chronoamperometry measurements) or a variation (in case of voltammetry measurements) of potential is applied to the working electrode with respect to the reference electrode. The measured current is the rate of transferred electrons as a function of time, being proportional to the concentration of the target analyte [71].
- Impedimetric: impedimetric biosensors measure the electrical impedance produced at the electrode interface when a small sinusoidal perturbation signal is applied. It involves the application of low amplitude AC voltage at the sensor electrode and then the current response is measured as a function of frequency using an impedance analyzer [64,72].
5.1. Voltammetry
Cyclic Voltammetry (CV)
5.2. Square Wave Voltammetry (SWV)
5.3. Electochemical Impedance Spectrocopy (EIS)
6. Types of a Bioreceptor
6.1. Enzymes
6.2. Antibodies
6.3. Molecularly Imprinted Polymers
7. Immobilization Techniques
8. Requirements of a Biosensor
- Selectivity: main requirement of a biosensor. It deals with the ability to recognize and detect the target analyte in the presence of other potentially interfering species. For such, biological recognition elements are immobilized on the surface of the transducer [101]. A factor that influences selectivity is biofouling, that is, accumulation of chemical species in the detection layer that gradually degrades the performance of the sensor. This effect can be reduced with the incorporation of semi-permeable membranes like cellulose acetate, for example and detect the target analyte in the presence of other potentially interfering species.
- Sensitivity (S): it is the measure of how sharply the signal changes with variations in the concentration of the target analyte. Calibration curves can be generated with the gradual increase of the concentration of the analyte with the aim of determining the sensitivity of the sensor through the slope of the curve obtained in cases where hysteresis is insignificant, as it shown in Equation (6). In the case of drug detection systems may only require binary information to determine the presence or absence of a drug above a predefined tolerance level. In such cases, the sensor does not need to have a very high sensitivity but should be able to distinguish concentrations above or below the threshold [101]. The use of materials such as carbon nanotubes or metal nanoparticles contributes to a better transfer of electrons and thus amplify detection.
- Detection Limit (LOD): indicates the lowest concentration which a sensor can detect and stems from signal-to-noise relationships. The signal noise-ratio with a value of 3.3. is generally acceptable [101]. Thus, the limit of detection (LOD) may be expressed by the Equation (7):
- Stability: refers to the sensor ability to maintain the signal over time. Hydrophobic materials can improve this property and conductive polymers such as polystyrene, polypyrrole and polyaniline improve even more stability. In addition, the immobilization of the bioreceptor through techniques such as crosslinking with polymers help to improve this ability. A balance must be achieved in order to optimize stability and sensitivity.
- Response time: sensor response time to stabilize at a reliable value when the concentration of the analyte change. Response times are typically influenced by target analyte, bioreceptor and sample composition. A lower thickness of the bioreceptor helps to decrease the response time.
- Reproducibility/Precision: the degree of reproducibility required depends on the sensitivity of the sensor [101]. Screen printing techniques allow the production of high-yield sensors with high uniformity. Refers to the ability of the sensor to maintain the signal over the time. The proximity between several measurements performed on the same sample in different days/conditions is generally obtained through the coefficient of variation (CV) expressed by the Equation (8).
- Linearity: it is necessary to use enough standard solutions (minimum 5) of to adequately define the relationship between concentration and response. Linearity refers to the ability to generate results linearly proportional to the concentration of the target analyte. This parameter can be obtained through the Pearson correlation index acquired through the calibration curve performed. It is known that the closer to one the absolute value of this coefficient is, the stronger the linear relationship between the two variables to analyze is [101]. The linear range corresponds to the target analyte concentration range the obtained response is linear.
9. Construction of Flexible Biosensors
9.1. Screen Printed Electrodes
SPEs Process of Formation: Substrates, Inks and Additives
10. Outlook and Future Scope
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Conflicts of Interest
References
- WHO Kicks off a Decade of Action for Road Safety. 2021. Available online: https://www.who.int/news/item/28-10-2021-who-kicks-off-a-decade-of-action-for-road-safety (accessed on 1 April 2022).
- Simões, M.T.B.d. Fatores de Risco Auto Reportados Associados aos Acidentes Rodoviários: Um Estudo Sobre os Condutores Portugueses de Veículos Ligeiros. 2014. Available online: https://run.unl.pt/handle/10362/14807 (accessed on 19 December 2021).
- WHO. 2018. Available online: https://www.who.int/news-room/fact-sheets/detail/alcohol (accessed on 8 March 2022).
- Azevedo, A.M.; Miguel, D.; Prazeres, F.; Cabral, J.M.S.; Fonseca, L.P. Ethanol biosensors based on alcohol oxidase. Biosens. Bioelectron. 2005, 21, 235–247. [Google Scholar] [CrossRef] [PubMed]
- Fekete, A. Identification of Bacterial N-Acylhomoserine Lactones (AHLs) with a Combination of Ultra-Performance Liquid Chromatography (UPLC), Ultra-High-Resolution Mass Spectrometry, and In-Situ Biosensors; Springer: Berlin/Heidelberg, Germany, 2006. [Google Scholar] [CrossRef]
- Jenkins, A.J. Drug Testing in Alternate Biological Specimens; Humana Press: Totowa, NJ, USA, 2008. [Google Scholar] [CrossRef]
- Campbell, A.S.; Kim, J.; Wang, J. Wearable electrochemical alcohol biosensors. Curr. Opin. Electrochem. 2018, 10, 126–135. [Google Scholar] [CrossRef] [PubMed]
- RAli, S.S.; Wilson, M.P.; Castillo, E.M.; Witucki, P.; Simmons, T.T.; Vilke, G.M. Common Hand Sanitizer May Distort Readings of Breathalyzer Tests in the Absence of Acute Intoxication. Acad. Emerg. Med. 2013, 20, 212–215. [Google Scholar] [CrossRef]
- Caravati, E.M.; Anderson, K.T. Breath Alcohol Analyzer Mistakes Methanol Poisoning for Alcohol Intoxication. Ann. Emerg. Med. 2010, 55, 198–200. [Google Scholar] [CrossRef] [PubMed]
- Raza, T.; Qu, L.; Khokhar, W.A.; Andrews, B.; Ali, A.; Tian, M. Progress of Wearable and Flexible Electrochemical Biosensors with the Aid of Conductive Nanomaterials. Front. Bioeng. Biotechnol. 2021, 9, 761020. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.; Xu, H.; Zhang, J.; Li, G. Electrochemical Sensors for Clinic Analysis. Sensors 2008, 8, 2043–2081. [Google Scholar] [CrossRef] [Green Version]
- Li, Q.; Wu, J.-T.; Liu, Y.; Qi, X.-M.; Jin, H.-G.; Yang, C.; Liu, J.; Li, G.-L.; He, Q.-G. Recent advances in black phosphorus-based electrochemical sensors: A review. Anal. Chim. Acta 2021, 1170, 338480. [Google Scholar] [CrossRef]
- Buono, M.J. Sweat Ethanol Concentrations are Highly Correlated with Co-Existing Blood Values in Humans. Exp. Physiol. 1999, 84, 401–404. [Google Scholar] [CrossRef]
- Kamei, T.; Tsuda, T.; Mibu, Y.; Kitagawa, S.; Wada, H.; Naitoh, K.; Nakashima, K. Novel instrumentation for determination of ethanol concentrations in human perspiration by gas chromatography and a good interrelationship between ethanol concentrations in sweat and blood. Anal. Chim. Acta 1998, 365, 259–266. [Google Scholar] [CrossRef]
- Wang, J. Analytical Electrochemistry, 3rd ed.; Wiley-VCH: New York, NY, USA, 2006; Available online: https://www.wiley.com/en-us/Analytical+Electrochemistry%2C+3rd+Edition-p-9780471678793 (accessed on 5 April 2022).
- Litten, R.Z.; Bradley, A.M.; Moss, H.B. Alcohol Biomarkers in Applied Settings: Recent Advances and Future Research Opportunities. Alcohol. Clin. Exp. Res. 2010, 34, 955–967. [Google Scholar] [CrossRef]
- Bearer, C.F.; Bailey, S.M.; Hoek, J.B. Advancing Alcohol Biomarkers Research. Alcohol. Clin. Exp. Res. 2010, 34, 941–945. [Google Scholar] [CrossRef] [PubMed]
- Akkari, A.C.S.; de Lima, E.C. Padronização de Informações Sobre Metodologias Analíticas para a Determinação dos Níveis de Álcool (Etanol) em Diferentes Amostras Biológicas. 2009, pp. 1–3. Available online: https://www.researchgate.net/publication/351275061 (accessed on 19 December 2021).
- Jones, A.W. Measuring Alcohol in Blood and Breath for Forensic Purposes-A Historical Review Theory and Practice of Forensic Breath Alcohol Analysis View Project Forensic Blood Alcohol Calculations View Project. 1996. Available online: https://www.researchgate.net/publication/281174460 (accessed on 19 March 2022).
- Niemelä, O. Invited critical review Biomarkers in alcoholism. Clin. Chim. Acta 2006, 377, 39–49. [Google Scholar] [CrossRef] [PubMed]
- Thierauf, A.; Wohlfarth, A.; Auwärter, V.; Perdekamp, M.G.; Wurst, F.M.; Weinmann, W. Urine tested positive for ethyl glucuronide and ethyl sulfate after the consumption of yeast and sugar. Forensic Sci. Int. 2010, 202, e45–e47. [Google Scholar] [CrossRef] [PubMed]
- Kissack, J.C.; Bishop, J.; Roper, A.L. Ethylglucuronide as a Biomarker for Ethanol Detection. Pharmacother. J. Hum. Pharmacol. Drug Ther. 2008, 28, 769–781. [Google Scholar] [CrossRef]
- Selvam, A.P.; Muthukumar, S.; Kamakoti, V.; Prasad, S. A wearable biochemical sensor for monitoring alcohol consumption lifestyle through Ethyl glucuronide (EtG) detection in human sweat. Sci. Rep. 2016, 6, 23111. [Google Scholar] [CrossRef]
- Høiseth, G.; Morini, L.; Polettini, A.; Christophersen, A.; Mørland, J. Ethyl Glucuronide in Hair Compared with Traditional Alcohol Biomarkers—A Pilot Study of Heavy Drinkers Referred to an Alcohol Detoxification Unit. Alcohol. Clin. Exp. Res. 2009, 33, 812–816. [Google Scholar] [CrossRef]
- Junghanns, K.; Graf, I.; Pflüger, J.; Wetterling, G.; Ziems, C.; Ehrenthal, D.; Zöllner, M.; Dibbelt, L.; Backhaus, J.; Weinmann, W.; et al. Urinary ethyl glucuronide (EtG) and ethyl sulphate (EtS) assessment: Valuable tools to improve verification of abstention in alcohol-dependent patients during in-patient treatment and at follow-ups. Addiction 2009, 104, 921–926. [Google Scholar] [CrossRef]
- González-Illán, F.; Ojeda-Torres, G.; Díaz-Vázquez, L.M.; Rosario, O. Detection of fatty acid ethyl esters in skin surface lipids as biomarkers of ethanol consumption in alcoholics, social drinkers, light drinkers, and teetotalers using a methodology based on microwave-assisted extraction followed by solid-phase microextraction and gas chromatography-mass spectrometry. J. Anal. Toxicol. 2011, 35, 232–237. [Google Scholar] [CrossRef] [Green Version]
- Waszkiewicz, N.; Szajda, S.D.; Kȩpka, A.; Szulc, A.; Zwierz, K. Glycoconjugates in the detection of alcohol abuse. Biochem. Soc. Trans. 2011, 39, 365–369. [Google Scholar] [CrossRef]
- Tavakoli, H.R.; Hull, M.; Okasinski, L.T.M. Review of Current Clinical Biomarkers for the Detection of Alcohol Dependence. Innov. Clin. Neurosci. 2022, 8, 26. [Google Scholar]
- Reif, A.; Fallgatter, A.J.; Schmidtke, A. Carbohydrate-deficient transferrin parallels disease severity in anorexia nervosa. Psychiatry Res. 2005, 137, 143–146. [Google Scholar] [CrossRef] [PubMed]
- Kenan, N.; Larsson, A.; Axelsson, O.; Helander, A. Changes in transferrin glycosylation during pregnancy may lead to false-positive carbohydrate-deficient transferrin (CDT) results in testing for riskful alcohol consumption. Clin. Chim. Acta 2011, 412, 129–133. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Javors, M.A.; Johnson, B.A. Current status of carbohydrate deficient transferrin, total serum sialic acid, sialic acid index of apolipoprotein J and serum β-hexosaminidase as markers for alcohol consumption. Addiction 2003, 98, 45–50. [Google Scholar] [CrossRef] [PubMed]
- Hannuksela, M.L.; Liisanantti, M.K.; Nissinen, A.E.T.; Savolainen, M.J. Biochemical markers of alcoholism. Clin. Chem. Lab. Med. 2007, 45, 953–961. [Google Scholar] [CrossRef]
- Kärkkäinen, P.; Poikolainen, K.; Salaspuro, M. Serum β-Hexosaminidase as a Marker of Heavy Drinking. Alcohol. Clin. Exp. Res. 1990, 14, 187–190. [Google Scholar] [CrossRef]
- Nanau, R.M.; Neuman, M.G.; Osna, N.; Kharbanda, K. Biomolecules and Biomarkers Used in Diagnosis of Alcohol Drinking and in Monitoring Therapeutic InterventionsBiomolecules and Biomarkers Used in Diagnosis of Alcohol Drinking and in Monitoring Therapeutic Interventions. Biomolecules 2010, 5, 1339–1385. [Google Scholar] [CrossRef] [Green Version]
- Teymourian, H.; Moonla, C.; Tehrani, F.; Vargas, E.; Aghavali, R.; Barfidokht, A.; Tangkuaram, T.; Mercier, P.P.; Dassau, E.; Wang, J. Microneedle-Based Detection of Ketone Bodies along with Glucose and Lactate: Toward Real-Time Continuous Interstitial Fluid Monitoring of Diabetic Ketosis and Ketoacidosis. Anal. Chem. 2020, 92, 2291–2300. [Google Scholar] [CrossRef]
- Martín, A.; Kim, J.; Kurniawan, J.F.; Sempionatto, J.R.; Moreto, J.R.; Tang, G.; Campbell, A.S.; Shin, A.; Lee, M.Y.; Liu, X.; et al. Epidermal Microfluidic Electrochemical Detection System: Enhanced Sweat Sampling and Metabolite Detection. ACS Sens. 2017, 2, 1860–1868. [Google Scholar] [CrossRef]
- Sekar, M.; Pandiaraj, M.; Bhansali, S.; Ponpandian, N.; Viswanathan, C. Carbon fiber based electrochemical sensor for sweat cortisol measurement. Sci. Rep. 2019, 9, 403. [Google Scholar] [CrossRef] [Green Version]
- Rahman, M.M. Selective capturing of phenolic derivative by a binary metal oxide microcubes for its detection. Sci. Rep. 2019, 9, 19234. [Google Scholar] [CrossRef] [Green Version]
- Rahman, M.M.; Karim, M.R.; Alam, M.M.; Zaman, M.B.; Alharthi, N.; Alharbi, H.; Asiri, A.M. Facile and efficient 3-chlorophenol sensor development based on photolumenescent core-shell CdSe/ZnS quantum dots. Sci. Rep. 2020, 10, 557. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Rahman, M.M.; Khan, S.B.; Gruner, G.; Al-Ghamdi, M.S.; Daous, M.A.; Asiri, A.M. Chloride ion sensors based on low-dimensional α-MnO2–Co3O4 nanoparticles fabricated glassy carbon electrodes by simple I–V technique. Electrochim. Acta 2013, 103, 143–150. [Google Scholar] [CrossRef]
- Sekine, Y.; Kim, S.B.; Zhang, Y.; Bandodkar, A.J.; Xu, S.; Choi, J.; Irie, M.; Ray, T.R.; Kohli, P.; Kozai, N.; et al. A fluorometric skin-interfaced microfluidic device and smartphone imaging module for in situ quantitative analysis of sweat chemistry. Lab Chip 2018, 18, 2178–2186. [Google Scholar] [CrossRef] [PubMed]
- Sempionatto, J.R.; Martin, A.; García-Carmona, L.; Barfidokht, A.; Kurniawan, J.F.; Moreto, J.R.; Tang, G.; Shin, A.; Liu, X.; Escarpa, A.; et al. Skin-worn Soft Microfluidic Potentiometric Detection System. Electroanalysis 2019, 31, 239–245. [Google Scholar] [CrossRef]
- Bariya, M.; Nyein, H.Y.Y.; Javey, A. Wearable sweat sensors. Nat. Electron. 2018, 1, 160–171. [Google Scholar] [CrossRef]
- Legner, C.; Kalwa, U.; Patel, V.; Chesmore, A.; Pandey, S. Sweat sensing in the smart wearables era: Towards integrative, multifunctional and body-compliant perspiration analysis. Sens. Actuators A Phys. 2019, 296, 200–221. [Google Scholar] [CrossRef]
- Moyer, J.; Wilson, D.; Finkelshtein, I.; Wong, B.; Potts, R. Correlation Between Sweat Glucose and Blood Glucose in Subjects with Diabetes. Diabetes Technol. Ther. 2012, 14, 398–402. [Google Scholar] [CrossRef]
- Sakharov, D.A.; Shkurnikov, M.; Vagin, M.; Yashina, E.I.; Karyakin, A.; Tonevitsky, A. Relationship between Lactate Concentrations in Active Muscle Sweat and Whole Blood. Bull. Exp. Biol. Med. 2010, 150, 83–85. [Google Scholar] [CrossRef]
- Alvear-Ordenes, I.; García-López, D.; de Paz, J.A.; González-Gallego, J. Sweat lactate, ammonia, and urea in rugby players. Int. J. Sport. Med. 2005, 26, 632–637. [Google Scholar] [CrossRef]
- Hair, M.E.; Gerkman, R.; Mathis, A.I.; Halámková, L.; Halámek, J. Noninvasive Concept for Optical Ethanol Sensing on the Skin Surface with Camera-Based Quantification. Anal. Chem. 2019, 91, 15860–15865. [Google Scholar] [CrossRef]
- Toma, K.; Suzuki, S.; Arakawa, T.; Iwasaki, Y.; Mitsubayashi, K. External ears for non-invasive and stable monitoring of volatile organic compounds in human blood. Sci. Rep. 2021, 11, 10415. [Google Scholar] [CrossRef] [PubMed]
- Zhong, B.; Jiang, K.; Wang, L.; Shen, G. Wearable Sweat Loss Measuring Devices: From the Role of Sweat Loss to Advanced Mechanisms and Designs. Adv. Sci. 2022, 9, 2103257. [Google Scholar] [CrossRef] [PubMed]
- Webster, G.D.; Gabler, H.C. Feasibility of transdermal ethanol sensing for the detection of intoxicated drivers. Annu. Proc. Assoc. Adv. Automot. Med. 2007, 51, 449–464. [Google Scholar] [PubMed]
- Schober, P.; Boer, C.; Schwarte, L.A. Correlation Coefficients: Appropriate Use and Interpretation. Anesth. Analg. 2018, 126, 1763–1768. [Google Scholar] [CrossRef]
- Nyman, E.; Palmlöv, A. The Elimination of Ethyl Alcohol in Sweat1. Skand. Arch. Physiol. 1936, 74, 155–159. [Google Scholar] [CrossRef]
- Barnett, N.P.; Tidey, J.; Murphy, J.G.; Swift, R.; Colby, S.M. Contingency management for alcohol use reduction: A pilot study using a transdermal alcohol sensor. Drug Alcohol Depend. 2011, 118, 391–399. [Google Scholar] [CrossRef] [Green Version]
- Marques, P. Evaluating TransdErmal Alcohol mEasuring dEvicEs Final Report. 2007. Available online: www.nhtsa.dot.gov (accessed on 13 December 2021).
- (PDF) In Vivo Evaluation of BACtrack® Skyn: A Discrete Wrist-Worn Transdermal Alcohol Monitoring Device Marketed to the Public. Available online: https://www.researchgate.net/publication/356696470_In_vivo_evaluation_of_BACtrackR_Skyn_a_discrete_wrist-worn_transdermal_alcohol_monitoring_device_marketed_to_the_public (accessed on 1 April 2022).
- Wang, Y.; Fridberg, D.J.; Leeman, R.F.; Cook, R.L.; Porges, E.C. Wrist-worn alcohol biosensors: Strengths, limitations, and future directions. Alcohol 2019, 81, 83–92. [Google Scholar] [CrossRef]
- Kim, J.; Jeerapan, I.; Imani, S.; Cho, T.N.; Bandodkar, A.J.; Cinti, S.; Mercier, P.; Wang, J. Noninvasive Alcohol Monitoring Using a Wearable Tattoo-Based Iontophoretic-Biosensing System. ACS Sens. 2016, 1, 1011–1019. [Google Scholar] [CrossRef]
- Christie, G.; Gual, A.; Nicola, M.; Davis-Martin, R.E.; Alessi, S.M.; Boudreaux, E.D. Alcohol Use Disorder in the Age of Technology: A Review of Wearable Biosensors in Alcohol Use Disorder Treatment. Front. Psychiatry 2021, 12, 642813. [Google Scholar] [CrossRef]
- Lee, S.I.; Nam, H.S.; Garst, J.H.; Huang, A.; Campion, A.; Arnell, M.; Ghalehsariand, N.; Park, S.; Chang, H.-J.; Lu, D.C.; et al. Unobtrusive and Continuous Monitoring of Alcohol-impaired Gait Using Smart Shoes. Methods Inf. Med. 2017, 56, 74–82. [Google Scholar] [CrossRef] [Green Version]
- Turner, A.P.F. Biosensors: Sense and sensibility. Chem. Soc. Rev. 2013, 42, 3184–3196. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Chung, M.; Fortunato, G.; Radacsi, N. Wearable flexible sweat sensors for healthcare monitoring: A review. J. R. Soc. Interface 2019, 16, 20190217. [Google Scholar] [CrossRef] [PubMed]
- Karunakaran, C.; Rajkumar, R.; Bhargava, K. Introduction to Biosensors. Biosens. Bioelectron. 2015, 1–68. [Google Scholar] [CrossRef]
- Charoenkitamorn, K.; Yakoh, A.; Jampasa, S.; Chaiyo, S.; Chailapakul, O. Electrochemical and optical biosensors for biological sensing applications. Science 2020, 46, 245. [Google Scholar] [CrossRef]
- Ramanathan, K.; Danielsson, B. Principles and applications of thermal biosensors. Biosens. Bioelectron. 2001, 16, 417–423. [Google Scholar] [CrossRef]
- Pohanka, M. Overview of Piezoelectric Biosensors, Immunosensors and DNA Sensors and Their Applications. Materials 2018, 11, 448. [Google Scholar] [CrossRef] [Green Version]
- Grieshaber, D.; Mackenzie, R.; Vörös, J.; Reimhult, E. Electrochemical Biosensors-Sensor Principles and Architectures. Sensors 2008, 8, 1400–1458. [Google Scholar] [CrossRef]
- Naresh, V.; Lee, N. A Review on Biosensors and Recent Development of Nanostructured Materials-Enabled Biosensors. Sensors 2021, 21, 1109. [Google Scholar] [CrossRef]
- Cesewski, E.; Johnson, B.N. Electrochemical biosensors for pathogen detection. Biosens. Bioelectron. 2020, 159, 112214. [Google Scholar] [CrossRef]
- Alaejos, M.S.; Montelongo, F.J.G. Application of Amperometric Biosensors to the Determination of Vitamins and α-Amino Acids. Chem. Rev. 2004, 104, 3239–3266. [Google Scholar] [CrossRef]
- Faulkner, L.R.; Bard, J.A. Fundamentals and Applications. Annu. Rev. Mater. Sci. 2000, 30, 30–100. [Google Scholar]
- Zhang, H.; Li, X.; Zhu, Q.; Wang, Z. The recent development of nanomaterials enhanced paper-based electrochemical analytical devices. J. Electroanal. Chem. 2022, 909, 116140. [Google Scholar] [CrossRef]
- Brett, C.M.A.; Brett, A.M.O. Electrochemistry: Principles, Methods, and Applications; Oxford University Press: Oxford, UK, 1993. [Google Scholar]
- Levi, M.; Gamolsky, K.; Aurbach, D.; Heider, U.; Oesten, R. On electrochemical impedance measurements of LixCo0.2Ni0.8O2 and LixNiO2 intercalation electrodes. Electrochim. Acta 2000, 45, 1781–1789. [Google Scholar] [CrossRef]
- Jackson, A.; Bosco, T. Desenvolvimento de Biossensor Eletroquímico paraDeteção do Biocombustível Etanol. 2005. Available online: http://epqb.eq.ufrj.br/wp-content/uploads/2021/04/15_51.pdf (accessed on 22 March 2022).
- Skoog; West; Holler; Crouch; Fundamentos de Química Analítica. 2005; Volume 80. Available online: https://www.inesul.edu.br/site/documentos/QUIMICA_ANALITICA_SKOOG.pdf (accessed on 11 January 2022).
- Royal Society of Chemistry. Chemistry for Biologists Enzymes. 2004. Available online: https://www.rsc.org/Education/Teachers/Resources/cfb/enzymes.htm (accessed on 22 March 2022).
- Leote, R.J.; Brettr, C.; Ghica, M.E. Desenvolvimento e Caracterização de Biossensores Eletroquímicos Enzimáticos com Enzimas Oxidase; Coimbra University: Coimbra, Portugal, 2017. [Google Scholar]
- Bucur, B.; Purcarea, C.; Andreescu, S.; Vasilescu, A. Addressing the Selectivity of Enzyme Biosensors: Solutions and Perspectives. Sensors 2021, 21, 3038. [Google Scholar] [CrossRef] [PubMed]
- Morales, M.; Halpern, J.M. Guide to Selecting a Biorecognition Element for Biosensors. Bioconjug. Chem. 2018, 29, 3231–3239. [Google Scholar] [CrossRef]
- Guc, M.; Schroeder, G. The Molecularly Imprinted Polymers. Influence of Monomers on The Properties of Polymers-A Review. 2017, p. 36. Available online: https://www.wjrr.org/download_data/WJRR0506008.pdf (accessed on 7 January 2022).
- Sharma, P.S.; Dąbrowski, M.; D’Souza, F.; Kutner, W. Surface development of molecularly imprinted polymer films to enhance sensing signals. TrAC Trends Anal. Chem. 2013, 51, 146–157. [Google Scholar] [CrossRef]
- Cormack, P.A.; Elorza, A.Z. Molecularly imprinted polymers: Synthesis and characterisation. J. Chromatogr. B 2004, 804, 173–182. [Google Scholar] [CrossRef]
- Crapnell, D. Recent Advances in Electrosynthesized Molecularly Imprinted Polymer Sensing Platforms for Bioanalyte Detection. Sensors 2019, 19, 1204. [Google Scholar] [CrossRef] [Green Version]
- Adumitrăchioaie, A.; Tertiş, M.; Cernat, A.; Săndulescu, R.; Cristea, C. Electrochemical Methods Based on Molecularly Imprinted Polymers for Drug Detection. A Review. Int. J. Electrochem. Sci. 2018, 13, 2556–2576. [Google Scholar] [CrossRef]
- Yan, M.; Ramström, O. Molecularly Imprinted Materials: Science and Technology; Marcel Dekker: New York, NY, USA, 2005. [Google Scholar]
- Pérez-Moral, N.; Mayes, A. Comparative study of imprinted polymer particles prepared by different polymerisation methods. Anal. Chim. Acta 2004, 504, 15–21. [Google Scholar] [CrossRef]
- Spivak, D.; Gilmore, A.M.A.; Shea, K.J. Evaluation of Binding and Origins of Specificity of 9-Ethyladenine Imprinted Polymers. J. Am. Chem. Soc. 1997, 119, 4388–4393. [Google Scholar] [CrossRef]
- Piletska, E.V.; Guerreiro, A.R.; Whitcombe, M.J.; Piletsky, S.A. Influence of the Polymerization Conditions on the Performance of Molecularly Imprinted Polymers. Macromolecules 2009, 42, 4921–4928. [Google Scholar] [CrossRef]
- Putzbach, W.; Ronkainen, N.J. Immobilization Techniques in the Fabrication of Nanomaterial-Based Electrochemical Biosensors: A Review. Sensors 2013, 13, 4811–4840. [Google Scholar] [CrossRef] [PubMed]
- Vasconcelos, H.; Coelho, L.C.C.; Matias, A.; Saraiva, C.; Jorge, P.A.S.; de Almeida, J.M.M.M. Biosensors for Biogenic Amines: A Review. Biosensors 2021, 11, 82. [Google Scholar] [CrossRef]
- Bié, J.; Sepodes, B.; Fernandes, P.C.B.; Ribeiro, M.H.L. Enzyme Immobilization and Co-Immobilization: Main Framework, Advances and Some Applications. Processes 2022, 10, 494. [Google Scholar] [CrossRef]
- Bhardwaj, T. A Review on Immobilization Techniques of Biosensors. Available online: www.ijert.org (accessed on 19 March 2022).
- Ahuja, T.; Mir, I.A.; Kumar, D. Rajesh Biomolecular immobilization on conducting polymers for biosensing applications. Biomaterials 2007, 28, 791–805. [Google Scholar] [CrossRef]
- Coelho, M.K.L.; Giarola, J.; Pereira, A.C. Electrochemical Sensors Based on Polymers Printed Molecularly and The Determination of Drugs in Pharmaceutical and Biological Samples. Rev. Virtual Quím. 2018, 10, 1180–1206. [Google Scholar] [CrossRef]
- Hassan, M.E.; Yang, Q.; Xiao, Z. Covalent immobilization of glucoamylase enzyme onto chemically activated surface of κ-carrageenan. Bull. Natl. Res. Cent. 2019, 43, 102. [Google Scholar] [CrossRef] [Green Version]
- Karakuş, E.; Pekyardimci, Ş. Comparison of Covalent and Noncovalent Immobilization of Malatya Apricot Pectinesterase (Prunus armeniaca L.). Artif. Cells Blood Substit. Biotechnol. 2012, 40, 132–141. [Google Scholar] [CrossRef]
- Gohary, N.A.; Madbouly, A.; Nashar, R.M.; Mizaikoff, B. Biosensors and Bioelectronics; Elsevier: Amsterdam, The Netherlands, 2015; Volume 65. [Google Scholar]
- Thévenot, D.R.; Toth, K.; Durst, R.A.; Wilson, G.S. Electrochemical biosensors: Recommended definitions and classification. Biosens. Bioelectron. 2001, 16, 121–131. [Google Scholar] [CrossRef]
- Validation of Analytical Procedures: Text and Methodology Q2(R1). 2014. Available online: www.somatek.com (accessed on 27 January 2022).
- Manousiouthakis, E.; Park, J.; Hardy, J.G.; Lee, J.Y.; Schmidt, E.C. Towards the translation of electroconductive organic materials for regeneration of neural tissues. Acta Biomater. 2022, 139, 22–42. [Google Scholar] [CrossRef] [PubMed]
- Hatamie, A.; Angizi, S.; Kumar, S.; Pandey, C.M.; Simchi, A.; Willander, M.; Malhotra, B.D. Review—Textile Based Chemical and Physical Sensors for Healthcare Monitoring. J. Electrochem. Soc. 2020, 167, 037546. [Google Scholar] [CrossRef]
- Kinnamon, D.S.; Krishnan, S.; Brosler, S.; Sun, E.; Prasad, S. Screen Printed Graphene Oxide Textile Biosensor for Applications in Inexpensive and Wearable Point-of-Exposure Detection of Influenza for At-Risk Populations. J. Electrochem. Soc. 2018, 165, B3084–B3090. [Google Scholar] [CrossRef]
- Gualandi, I.; Marzocchi, M.; Achilli, A.; Cavedale, D.; Bonfiglio, A.; Fraboni, B. Textile Organic Electrochemical Transistors as a Platform for Wearable Biosensors. Sci. Rep. 2016, 6, 33637. [Google Scholar] [CrossRef] [PubMed]
- Manjakkal, L.; Dang, W.; Yogeswaran, N.; Dahiya, R. Textile-Based Potentiometric Electrochemical pH Sensor for Wearable Applications. Biosensors 2019, 9, 14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wang, R.; Zhai, Q.; An, T.; Gong, S.; Cheng, W. Stretchable gold fiber-based wearable textile electrochemical biosensor for lactate monitoring in sweat. Talanta 2021, 222, 121484. [Google Scholar] [CrossRef]
- Jabbour, G.E.; Radspinner, R.; Peyghambarian, N. Screen Printing for the Fabrication of Organic Light-Emitting Devices. IEEE J. Sel. Top. Quantum Electron. 2001, 7, 769. [Google Scholar] [CrossRef]
- Taleat, Z.; Khoshroo, A.; Mazloum-Ardakani, M. Screen-printed electrodes for biosensing: A review (2008–2013). Mikrochim. Acta 2014, 181, 865–891. [Google Scholar] [CrossRef]
- DropSens: Screen-Printed Electrodes. 2018. Available online: https://www.dropsens.com/en/screen_printed_electrodes_pag.html (accessed on 3 January 2022).
- Mota, D.F.F.M. Aplicação de Enzimas em Biossensores para a Monitorização de Poluentes Metálicos em meio Aquoso. Available online: https://ubibliorum.ubi.pt/handle/10400.6/2475 (accessed on 11 March 2022).
- Pandey, R.R.; Chusuei, C.C. Carbon Nanotubes, Graphene, and Carbon Dots as Electrochemical Biosensing Composites. Molecules 2021, 26, 6674. [Google Scholar] [CrossRef]
- Ferrier, D.C.; Honeychurch, K.C. Carbon Nanotube (CNT)-Based Biosensors. Biosensors 2021, 11, 486. [Google Scholar] [CrossRef]
- Da Silva, E.T.S.G.; Souto, D.E.P.; Barragan, J.T.C.; Giarola, J.D.F.; De Moraes, A.C.M.; Kubota, L.T. Electrochemical Biosensors in Point-of-Care Devices: Recent Advances and Future Trends. ChemElectroChem 2017, 4, 778–794. [Google Scholar] [CrossRef]
- Liu, J.; Kang, Y.; Yin, S.; Song, B.; Wei, L.; Chen, L.; Shao, L. Zinc oxide nanoparticles induce toxic responses in human neuroblastoma SHSY5Y cells in a size-dependent manner. Int. J. Nanomed. 2017, 12, 8085–8099. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Song, M.; Lin, X.; Peng, Z.; Xu, S.; Jin, L.; Zheng, X.; Luo, H. Materials and Methods of Biosensor Interfaces with Stability. Front. Mater. 2021, 7, 583739. [Google Scholar] [CrossRef]
- Suvarnaphaet, P.; Pechprasarn, S. Graphene-Based Materials for Biosensors: A Review. Sensors 2017, 17, 2161. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Barton, J.; García, M.B.G.; Santos, D.H.; Fanjul-Bolado, P.; Ribotti, A.; McCaul, M.; Diamond, D.; Magni, P. Screen-printed electrodes for environmental monitoring of heavy metal ions: A review. Microchim. Acta 2016, 183, 503–517. [Google Scholar] [CrossRef]
- Cinti, S.; Basso, M.; Moscone, D.; Arduini, F. A paper-based nanomodified electrochemical biosensor for ethanol detection in beers. Anal. Chim. Acta 2017, 960, 123–130. [Google Scholar] [CrossRef]
- Jewell, E.; Hamblyn, S.; Claypole, T.; Gethin, D. Deposition of High Conductivity Low Silver Content Materials by Screen Printing. Coatings 2015, 5, 172–185. [Google Scholar] [CrossRef] [Green Version]
- Camargo, J.R.; Orzari, L.O.; Araújo, D.A.G.; de Oliveira, P.R.; Kalinke, C.; Rocha, D.P.; dos Santos, A.L.; Takeuchi, R.M.; Munoz, R.A.A.; Bonacin, J.A.; et al. Development of conductive inks for electrochemical sensors and biosensors. Microchem. J. 2021, 164, 105998. [Google Scholar] [CrossRef]
- Aydemir, C.; Altay, B.N.; Akyol, M. Surface analysis of polymer films for wettability and ink adhesion. Color Res. Appl. 2021, 46, 489–499. [Google Scholar] [CrossRef]
- Gomes, P.; Tama, D.; Carvalho, H.; Souto, A.P. Resistance variation of conductive ink applied by the screen printing technique on different substrates. Color. Technol. 2020, 136, 130–136. [Google Scholar] [CrossRef]
- Schuman, T.; Wolf, R.A. Effects of a DBD plasma discharge on bond strength. Surf. Interfaces 2020, 18, 100461. [Google Scholar] [CrossRef]
- Zille, A.; Oliveira, F.R.; Souto, A.P. Plasma Treatment in Textile Industry. Plasma Process. Polym. 2015, 12, 98–131. [Google Scholar] [CrossRef] [Green Version]
- Cui, G.; Yoo, J.H.; Lee, J.S.; Yoo, J.; Uhm, J.H.; Cha, G.S.; Nam, H. Effect of pre-treatment on the surface and electrochemical properties of screen-printed carbon paste electrodes. Analyst 2001, 126, 1399–1403. [Google Scholar] [CrossRef] [PubMed]
- Khaled, E.; Mohamed, G.G.; Awad, T. Disposal screen-printed carbon paste electrodes for the potentiometric titration of surfactants. Sens. Actuators B Chem. 2008, 135, 74–80. [Google Scholar] [CrossRef]
- Scheuer, C. Recent Advances in Upscalable Wet Methods and Ink Formulations for Printed Electronics. J. Mater. Chem. 2014, 2, 6436–6453. [Google Scholar] [CrossRef]
- Abbott, S. How to Be a Great Screen Printer. 2008. Available online: https://books.google.com.br/books?hl=pt-PT&lr=&id=cZkne0jLjsUC&oi=fnd&pg=PA8&dq=how+to+be+a+great+screen+printing+abbot&ots=eXMjOWTLoc&sig=CSwxFgVUGMsSyPU19YNh7UIp7Eo (accessed on 24 January 2022).
- Khan, M.S.; Misra, S.K.; Schwartz-Duval, A.S.; Daza, E.; Ostadhossein, F.; Bowman, M.; Jain, A.; Taylor, G.; McDonagh, D.; Labriola, L.T.; et al. Real-Time Monitoring of Post-Surgical and Post-Traumatic Eye Injuries Using Multilayered Electrical Biosensor Chip. ACS Appl. Mater. Interfaces 2017, 9, 8609–8622. [Google Scholar] [CrossRef]
Device | Localization | Testing Status and Availability | Ref. |
---|---|---|---|
SCRAMTM produced by Alcohol Monitoring Systems (AMS) in Littleton, USA. | Ankle | It is the most widely used wearable device in clinical research trials and has been adopted internationally by justice systems for court monitored sobriety since 1997, being the most representative alcohol biosensor nowadays. | [54] |
WristTasTM produced by GINER lab, in Newton, MA | Wrist | It was developed primarily for use in medical settings with more compliant subjects, but lacks the protocols for detecting results‘ tampering and has not yet been adapted for court use. Completed laboratory testing has been done to the device, but it is not currently commercially available. | [55] |
BACtrack Skyn produced by BACKtrack in San Francisco, California | Wrist | Newest generation of wrist biosensors. Is a bracelet capable of measuring alcohol levels through insensible sweat. Commercially available since 2015. | [56] |
ProofTM produced by Milo Sensors in Santa Bárbara, California, USA | Wrist | Bracelet that utilizes an enzymatic electrochemical biosensor cartridge for alcohol detection, which can be coupled to a Smartphone App that targets safe recreational alcohol consumption with an integrated social aspect. Discontinued after laboratory testing. | [57] |
Quantac Tally produced by Quantac Inc. in New York, USA | Wrist | Combines alcohol monitoring data in its coupled smartphone App with health-related metrics to inform the wearer of personalized insights into health impacts of their alcohol consumption. Discontinued after laboratory testing. | [58] |
Iontophoretic Biosensing System produced by Kim et.al in Departments of Nanoengineering and Electrical & Computer Engineering, University of San Diego, California, USA | Tatto on arm | Screen-printed commercial tatto paper with silver and silver chloride electrodes. The electronic system transfer the results via Bluetooth via the wearer’s mobile device. Currently in laboratory testing. | [59] |
AlcoWear produced by McAfee et al. in San Francisco, California, USA | Wrist | Gait smartphone AlcoGait application paired with any smart watch to measure accelerometer and gyroscope. Currently in laboratory testing. | [60] |
Sensor-equipped Smart Shoes produced by Eunjeong Park and his team, in University Departments of Los Angeles, California/Boston, Massachusetts, USA and Seol, Korea | Shoes | Gait using pressure sensors inserted in insole of shoe. Currently in laboratory testing. | [61] |
Platform | Target Analyte/Bioreceptor | Measurement Technique | Linear Range | Ref. |
---|---|---|---|---|
Electrochemical biosensor: flexible co-planar Au or ZnO integrated in PI from bonding | EtG/EtG antibody | Electrochemical Impedance Spectroscopy (EIS) | 2 × 10−6–2.17 mM | [23] |
Optical biosensor: polyethylene strip composed of two enzymes | Ethanol/Alcohol Oxidase (AOx) and Horseradish peroxidase (HRP) | Chronoamperometry | 0–54.23 mM | [48] |
Electrochemical biosensor: hydrogel adhesive with screen printed electrodes | Ethanol/AOx | Chronoamperometry | 3.0–36.0 mM | [59] |
Method | Description | Advantages | Disadvantages | Ref. |
---|---|---|---|---|
Potentiometry | It is based on the measurement of the potential difference of the working electrode and the reference electrode. This potential difference is formed when, for example, an antigen-antibody interaction occurs, and it is measured under practically zero current conditions. |
|
| [64,67,69] |
Chronoamperometry | Direct measurement of the redox reaction current under a constant potential applied to the working electrode. The measured current is the rate of transferred electrons as a function of time, being proportional to the concentration of the target analyte. |
|
| [43,69,74] |
Voltametry | It consists of applying a potential in the electrochemical cell, measuring the resulting current. Voltammetric methods can be divided into Cyclic Volametry (CV); Differential Pulse Voltammetry (DPV); Linear Scanning Voltammetry (LSV); Square Wave Voltammetry (SWV). |
|
| [69,74,75,76] |
Elechtrochemical Impedance Spectoscopy | Electrode impedance measurement. It characterizes the structure and function of electrodes, especially those that have been modified with biological material. |
|
| [69,75,77] |
Conductimetry | It measures the variation in electrical conductivity that occurs in biological processes and that is caused by changes that occur in the concentration of ionic species in solution. |
|
| [43,69] |
Technique | Caracteristics | Advantages | Disadvantages | References |
---|---|---|---|---|
Adsorption |
|
|
| [92,93] |
Crosslinking |
|
|
| [91,93,94] |
Entrapment |
|
|
| [93,95,96] |
Covalent |
|
|
| [93,97,98] |
Biosensor | Target Analyte | Bioreceptor | Materials | Linear Range | LOD | Ref. |
---|---|---|---|---|---|---|
Monitoring alcohol consumption through sweating | EtG | Antibody EtG |
| 0.001–100 μg/L | (Au) 1 μL/L (ZnO) 0.001 ug/L | [23] |
Applications in detecting the point of exposure to Influenza A virus | Influenza A | Antibody specific for the H1N1 Influenza A protein |
| 10 ng/mL– 10 μg/mL | 10 ng/mL | [103] |
Detection of redox active biomolecules in biological fluid with a textile organic electrochemical transducer | Adrenaline; Dopamine; Ascorbic Acid | N/I |
| Adrenaline: 10−4–10−2 (M) Dopamine: 3.10−5–5.10−4 (M) Ascorbic Acid: 2.10−6–3.10−5 (M) | Adrenaline: 0.78 ± 0.05 × 10−8 (M) Dopamine: 0.8 ± 0.1 × 10−8 (M) Ascorbic Acid: 1.1 ± 0.1 × 10−8 (M) | [104] |
pH monitoring to detect diseases such as diabetes | Glucose | Glucose Oxidase Enzyme |
| N/I | N/I | [105] |
Monitoring the lactate level in sweat to detect diseases such as heart/circulatory failure, metabolic/respiratory disorders | Lactate | Lactate Oxidase Enzyme |
| 0 mM– 30 mM | 0.137 mM | [106] |
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Costa, N.G.; Antunes, J.C.; Paleo, A.J.; Rocha, A.M. A Review on Flexible Electrochemical Biosensors to Monitor Alcohol in Sweat. Biosensors 2022, 12, 252. https://doi.org/10.3390/bios12040252
Costa NG, Antunes JC, Paleo AJ, Rocha AM. A Review on Flexible Electrochemical Biosensors to Monitor Alcohol in Sweat. Biosensors. 2022; 12(4):252. https://doi.org/10.3390/bios12040252
Chicago/Turabian StyleCosta, Nuna G., Joana C. Antunes, Antonio J. Paleo, and Ana M. Rocha. 2022. "A Review on Flexible Electrochemical Biosensors to Monitor Alcohol in Sweat" Biosensors 12, no. 4: 252. https://doi.org/10.3390/bios12040252
APA StyleCosta, N. G., Antunes, J. C., Paleo, A. J., & Rocha, A. M. (2022). A Review on Flexible Electrochemical Biosensors to Monitor Alcohol in Sweat. Biosensors, 12(4), 252. https://doi.org/10.3390/bios12040252